Leveraging Data Analytics To Discover New Opportunities

Challenges in technology to meet needs of the logistics sector and differentiating factors

Challenges in the logistics sector include supply chain volatility, uncertainty, complexity and ambiguity. Our industry can no longer fine tune processes in a reactive mode. Operating environments are increasingly unpredictable, with more demand and supply volatility. Supply chains are increasingly global in nature, are more fluid and interconnected, and are no longer as closely controlled, incorporating suppliers and service providers. Risk (from economic, regulatory, environmental, and political factors) is growing. Customer and product complexity is increasing. Companies must adapt to support a more synchronized value chain perspective, with greater visibility and traceability if not control.

Likewise, big data and analytics provide a deeper understanding of operational decisions in relation to growth and profitability, propelling the supply chain functions to have a full seat at the table in corporate strategy discussions. Not only do we use these capabilities in house, but also we provide digital products to our customers so that they can do the same.

“The areas in business environment where solutions do not yet exist or not up to the mark, and which if existed, would've made job easier”

I don't believe that we should rely exclusively on commercially available solutions to solve the sticky problems. There is great work happening in the start-up community, fantastic work happening at universities, and many other unconventional sources that can be tapped for solutions that are differentiating to our businesses. It is important for IT leaders to build a strong community of third parties from whom we can source innovative solutions as needed.

Technological trends impacting the logistics sector

Data-related trends are the most interesting and potentially impactful for our industry. Big data is important not just due to its volume and velocity but also its complexity and variety. We now have visibility that can translate into a time advantage (speed to market, expediting, faster cycle time, and so on). Predictive analytics help us leverage our data for competitive advantage – we can better serve our customers, discover new opportunities, expose variability and risk, reduce waste, reduce cycle times, better understand the costs of doing business, target new products or markets, and generally increase our agility. Predictive analytics facilitate segmented analysis – versus relying on averages which can mask opportunities and threats – so we can tailor our products to customers or clusters of customers. While none of this can replace the human factor, it does enable a higher level of analysis for us versus routine reporting. Data visualization is the last item I’ll mention here. Enhanced visualization allows us to marry the science of the data and the art of innovation that our people bring to our business. This is a shift from a reporting mindset toward game-changing analysis capability.